New genomic data hold the promise of revolutionizing our understanding and treatment of human disease, and hence of greatly influencing clinical practice. Multiple barriers stand between the acquisition of the data and realizing these and other benefits. In particular, powerful and well-characterized computational methods for deducing the disease relevant phenotypic impact of genomic variants are needed. Over fifty such methods already exist, but currently, even though some are already deployed in clinical practice, we do not know how well these perform on relevant genome interpretation tasks. Further, it is already clear that new and more sophisticated approaches must be developed to fully meet the new challenges. The Center for Critical Assessment of Genome Interpretation (C-CAGI) will address these needs, through ongoing objective evaluation of the state of the art in relating genetic information to phenotype, particularly the relationship between human genetic variation and health. These goals are embraced by three specific aims: 1. Assess the quality of current computational methods for interpreting genomic variation data, and highlight innovations & progress. Building on successful initial experiments in 2010, 2011 and 2013, C-CAGI will conduct community-wide experiments in which participants make bona fide blinded predictions of disease related phenotypes on the basis of genomic data. These are evaluated by independent assessors with access to the correct answers, to determine how well methods work both relatively and absolutely. These assessments will establish the state-of-the art and advance the field. 2. Guide future research efforts in computational genome interpretation and build a strong community for collaboration and interaction. C-CAGI aims to engage and expand the community of researchers interpreting the phenotypic impact of genomic variation with CAGI workshops, hackathons, tutorials, and other mechanisms. We hope to use CAGI to spur and recognize innovative approaches to the breadth of practical and clinical research. The C-CAGI will also encourage and commission experimental studies necessary for focused testing of the computational methods. C-CAGI operates on a robust ethical foundation in using human research participant data, supported by the CAGI Ethics Forum. 3. Broadly disseminate the results and conclusions from the CAGI experiments and analysis. C-CAGI aims to be the central resource for information on interpretation of genomic variation. This dissemination to the broader scientific and clinical community will be using its publications, best practice guides, and web resources, and through presentations, tutorials, and workshops at international meetings.